Computational Network Design from Functional Specifications

ACM SIGGRAPH 2016

Fan Bao

Daniel Fink

Abstract

Connectivity and layout of underlying networks largely determine agent behavior and usage in many environments. For example, transportation networks determine the flow of traffic in a neighborhood, whereas building floorplans determine the flow of people in a workspace. Designing such networks from scratch is challenging as even local network changes can have large global effects. We investigate how to computationally create networks starting from only high-level functional specifications. Such specifications can be in the form of network density, travel time versus network length, traffic type, destination location, etc. We propose an integer programming-based approach that guarantees that the resultant networks are valid by fulfilling all the specified hard constraints and that they score favorably in terms of the objective function. We evaluate our algorithm in two different design settings, street layout and floorplans to demonstrate that diverse networks can emerge purely from high-level functional specifications.

Results

We propose an algorithm that generates networks for design scenarios like mid-scale urban street layouts (a-c) and floorplans for office spaces (d). The user simply specifies an input mesh as the problem domain along with high-level specifications of the functions of the generated network. Examples include preference for interior-to-boundary traffic (a) or interior-to-interior traffic (b), networks with specified destinations (i.e., sinks) on the boundary (c,d) and local feature control, such as reducing T-junctions (b) or forbidding dead-ends (c). For (a-c), the average travel time (distance) for interior-to-boundary traffic as estimated by the traffic simulator SUMO is indicated in green.

Ovewview. For each sub-region, as determined by the input major roads, we generate layouts in three levels of decreasing coverage ranges. For each level, a rough street network is first generated by the IP-based approach (shown in gray). Afterwards, the geometry of the generated street network is refined by a smoothing process. Dead-ends are typically allowed only at the last level.

Diverse street layouts resulting from different functional specifications. The first two layouts are optimized for (a) minimal network lengths and (b) minimal travel distances to the boundary, using different specifications of the optimization weights. The travel distances are shown in the bottom-left corners. (c) A layout with a single exit on the left. We also prefer a tree-like structure for this case, which is realized by allowing deadends on the second (collector roads) level. (d) A layout that encourages through-traffic in the vertical direction. This is realized by enforcing a shortest path connecting the two user-specified vertices (green) without inner branches on the second level. Note that through-traffic in other directions (e.g., horizontal) is implicitly discouraged. (e) A network that better supports interior-to-interior traffic, realized by the point-to-point constraint with a user-specified partition.

Acknowledgements

We thank the reviewers for their comments and suggestions for improving the paper. Special thanks to Stephen Marshall and Benjamin Heydecker for sharing their knowledge, expertise, and experience regarding urban street network design and traffic planning, and to Carlos Molinero, Clmentine Cottineau and Elsa Arcaute for initial discussions. This work was supported in part by the ERC Starting Grant SmartGeometry (StG-2013-335373), Marie Curie CIG 303541, the National Science Foundation, Office of Sponsored Research (OSR) under Award No. OCRF-2014-CGR3-62140401, research funding from King Abdullah University of Science and Technology (KAUST), EPSRC Grant EP/K02339X/1 and EP/M023281/1, and National Natural Science Foundation of China (Nos. 61372168 and 61572502).